# Research Tools Guide ## Overview Three research tools available through MCP: | Tool | Best For | Cost | |------|----------|------| | **DataForSEO** | Structured SEO data (volumes, KD, SERP features) | Paid (~$0.50/session) | | **Brave Search** | Fast web search (news, Reddit, competitors) | Free | | **Perplexity** | AI synthesis ("what's known about X") | Free | **Strategy:** Use free tools liberally for discovery. Use DataForSEO strategically for validation. --- ## Tool Distribution by Agent | Agent | DataForSEO | Brave Search | Perplexity | |-------|------------|--------------|------------| | @spy | ✓ keywords, backlinks, LLM mentions | ✓ news, Reddit, HN | ✓ deep research | | @strategist | ✓ volumes, difficulty, intent | — | ✓ content landscape | | @seo | ✓ SERP, on-page, LLM responses | ✓ what ranks now | — | | @webmaster | — | ✓ competitor pages | ✓ messaging research | --- ## Brave Search ### When to Use - Breaking news about competitors - Community discussions (Reddit, HN, Twitter) - What's currently ranking for a keyword - Competitor content examples ### Query Patterns ``` "runware ai news" → competitor updates "site:reddit.com ai image api" → community pain points "site:dev.to placeholder images" → existing content "replicate.com pricing" → competitor pages ``` ### Example Workflow (@spy) ``` 1. brave_search: "runware ai" → recent news 2. brave_search: "site:reddit.com mcp image generation" → community sentiment 3. Synthesize findings into research/*.md ``` --- ## Perplexity ### When to Use - Understanding what's already written about a topic - Getting synthesized overview of a domain - Deep research questions - Competitive positioning analysis ### Query Patterns ``` "What tutorials exist about Next.js image optimization" → content landscape "How do AI image APIs position themselves to developers" → messaging analysis "What are developers saying about MCP servers" → sentiment synthesis "Comparison of placeholder image services" → competitive intel ``` ### Example Workflow (@strategist) ``` 1. perplexity: "What content exists about AI placeholder images" → landscape 2. DataForSEO: keyword research for gaps → validate demand 3. Decision: write or skip ``` ### Example Workflow (@webmaster) ``` 1. brave_search: "replicate.com pricing page" → see competitor pages 2. perplexity: "How do AI APIs explain pricing to developers" → messaging patterns 3. Create pages/*.md with informed positioning ``` --- ## DataForSEO ### Budget Protocol - **Per session limit:** $0.50 (unless user explicitly approves more) - **Monthly budget:** ~$10 - **Always report:** Show what API calls you're making and estimated cost ### Core Principle Start with seeds → expand with related → filter by opportunity → verify with SERP. Don't chase high-volume competitive keywords. Find gaps where we can win. --- ### For @spy: Competitive Intelligence **Competitor Keywords** ``` Tool: dataforseo_labs_google_ranked_keywords Use: See what keywords competitors rank for Target: fal.ai, replicate.com, runware.ai, cloudinary.com ``` **Backlink Analysis** ``` Tool: backlinks_summary, backlinks_referring_domains Use: Where competitors get links, potential outreach targets ``` **Domain Intersection** ``` Tool: dataforseo_labs_google_domain_intersection Use: Find keywords multiple competitors rank for (validated demand) ``` **LLM Mentions (GEO)** ``` Tool: ai_optimization_llm_mentions_search Use: Check if Banatie or competitors mentioned in AI responses Platform: chat_gpt, google (AI Overview) ``` --- ### For @strategist: Keyword Research **Search Volume** ``` Tool: keywords_data_google_ads_search_volume Use: Get real monthly search volume for keyword list Input: Up to 1000 keywords per request ``` **Keyword Difficulty** ``` Tool: dataforseo_labs_bulk_keyword_difficulty Use: Score 0-100, lower = easier to rank Filter: KD < 50 for realistic targets ``` **Related Keywords** ``` Tool: dataforseo_labs_google_related_keywords Use: Expand seed keywords, find long-tail opportunities Depth: 1-4 (start with 1, go deeper if needed) ``` **Search Intent** ``` Tool: dataforseo_labs_search_intent Use: Classify keywords as informational/navigational/commercial/transactional Match: Content type should match intent ``` **AI Search Volume (GEO Priority)** ``` Tool: ai_optimization_keyword_data_search_volume Use: Keywords popular in AI search (ChatGPT, Perplexity) Why: Early indicator of emerging queries ``` **Research Workflow** 1. Start with seeds (3-5 per topic) 2. Get search volume for seeds 3. Expand top 3 by volume with related keywords 4. Filter: Volume > 50, KD < 50 5. Check intent for finalists 6. SERP analysis for top candidates --- ### For @seo: Optimization & Verification **SERP Analysis** ``` Tool: serp_organic_live_advanced Use: See current top 10 results, SERP features present Check: Featured snippets, PAA, video results ``` **On-Page Analysis** ``` Tool: on_page_instant_pages Use: Technical SEO check of specific URL After: Publishing, verify optimization ``` **LLM Responses (GEO)** ``` Tool: ai_optimization_llm_response Use: See how AI models answer our target queries Why: Optimize content for AI citations ``` --- ## Key Learnings **Problem-aware keywords often have zero volume.** People search for solutions, not problems. "placeholder images slow" = 0 volume. "generate images api" = real volume. **Related keywords > seed keywords.** Your initial guesses are rarely the best targets. Let data guide expansion. **Brand keywords are useless.** "cloudinary pricing" means they already chose Cloudinary. Target problem/solution queries. **Low KD + decent volume = opportunity.** Don't chase "ai image generation" (KD 80+). Find "generate images for nextjs" (KD 30, volume 200). --- ## Output Format When reporting research: ```markdown ## Research: [Topic] ### Tools Used - Brave Search: [queries] - Perplexity: [queries] - DataForSEO: [tools, estimated cost] ### Findings [What you discovered] ### Keywords (if applicable) | Keyword | Volume | KD | Intent | |---------|--------|----|----| | ... | ... | ... | ... | ### Recommendations [What to do next] ```